df_list_connections

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already mark the tool as read-only and idempotent, so the safety profile is covered. The description adds valuable behavioral context by stating that credentials are never returned and unsupported engines are excluded entirely.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The primary purpose is front-loaded, and the security-relevant caveat about credentials is appropriately placed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The core listing behavior and key exclusions are clear, but the tool has eight parameters and no output schema. Optional filtering, pagination, language, and caching behavior are left entirely to schema defaults and enums, which is adequate but minimal.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, so the description must compensate for six undocumented parameters, but it does not. It never clarifies page, status, db_type, language, page_size, or use_cache; the single note about unsupported engines is a behavioral detail, not parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'List database connections of a project version.' It is unambiguous and naturally distinguishes this tool from sibling tools like df_list_git_connections by limiting scope to database connections.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states the core action but provides no guidance on when to choose it over alternatives such as df_get_connection or df_get_connection_schema. No exclusions, conditions, or mention of related tools are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.